flowcytometry &cytolytics (8)

Flow Cyotmetric Immunophenotyping

Immunophenotyping enables the classification of cells beyond purely morphological assessment using the identification of cell membrane and intracellular antigens and is thus a central component of hematological diagnostics. In this examination, leukocytes are stained and sorted using immunological markers. The fluorescent dyes used allow differentiated and precise differentiation of individual leukocytes according to function and maturation stag.

What is immunophenotyping?

 

Cells of the hematopoietic system can be characterized by the detection of surface proteins. These surface proteins are usually specified according to the CD (cluster of differentiation) nomenclature. The detection of surface proteins is performed by specific antibodies coupled to a fluorescent dye. The detection of surface proteins is performed by specific antibodies. This method, which allows the measurement of antigens on a large number of blood cells in a very short time, is called flow cytometry. If, for example, lymphocytic populations are difficult to distinguish from one another under the microscope, flow cytometry can be used to quantify the ratio and number of immune cells or other cell populations of the blood or bone marrow. Immunophysiologically, different tasks can be assigned to the lymphocyte populations. Last but not least, importantimmunohistologicall findings in humans have been obtained by correlating the clinical phenotype (tendency to infection, pathogen spectrum) with the absence of certain cell populations in patients.

What is meant by Cluster of Differentiation (CD)?

 

CD molecules are membrane-bound glycoproteins, some of which are expressed in a cell-specific manner and can have a wide variety of functions: Some CDs have receptor or signaling functions, while others have been shown to have enzymatic activity. Also, some cluster molecules are thought to play a central role in intercellular communication. To date, several hundred molecules have been characterized, and it can be assumed that many more CDs exist.

What is the flow cytometry procedure for immunophenotyping?

 

The test material is usually peripheral blood and/or bone marrow, but other fluids e.g. cerebrospinal fluid or pleural effusion can also be used for testing. Based on the antigen profile of the analyzed cells, the lineage affiliation (myeloid vs. lymphoid) and the degree of differentiation can be determined. Modern multiparametric flow cytometry is based largely on advances in three areas: Laser optics, computerized data processing, and the development of new fluorescent dyes for coupling to the corresponding monoclonal antibodies. Membrane glycoproteins are detected by flow cytometry with fluorescently labeled monoclonal antibodies, usually using a combination of three or four different fluorochrome-labeled antibodies to characterize the cells. When several fluorescent dye-labeled antibodies are combined and the different scattering light properties of cells are exploited, it is possible to classify malignant hematologic neoplasms and, if necessary, to assess the success of therapy in the context of follow-up and minimal residual disease (MRD) control.

Membrane glycoproteins are detected by flow cytometry with fluorescently labeled monoclonal antibodies, usually using a combination of three or four different fluorochrome-labeled antibodies to characterize the cells. When several fluorescent dye-labeled antibodies are combined and the different scattering light properties of cells are exploited, it is possible to classify malignant hematologic neoplasms and, if necessary, to assess the success of therapy in the context of follow-up and minimal residual disease (MRD) control.

What innovation does Cytolytics offer?

 

Cytolytics offers sequential gating for detailed analysis, a graphical user interface for different computers, and a plausibly explained and understandable software language, as well as full automation of the analysis in flow cytometry. With the help of the innovation of full automation, not only large data sets are compared, but also abnormalities, anomalies, and outliers are detected based on the standardized setting. The automated analysis provides a standardized evaluation option so that familiarization with the Cytolytics software is effortless. The automated result documentation can be exported to various applications such as PPT, Word, and Excel, and a result presentation is possible directly and quickly without reprocessing. Using full automation, not only fast evaluations but also comparable, valid, repeatable, and meaningful results are delivered. With today’s technology, FACTS can identify which tumor and which cells are affected in the case of a cancer diagnosis. However, due to the time-consuming nature of gating, therapy planning and corresponding therapy control examinations often take place under great time pressure. Time is a life-saving factor and can, in sufficient quantities, enable precise, targeted therapy planning, for example in the case of leukemia. Cytolytics provides an innovative and intelligent solution for this. With time-saving analysis without gating, more time is available for planning therapies for life-threatening diseases and for preparing as well as publishing research.

About the author
Elif Karakurt
medical content creator
Elif is a medical student and works for Cytolytics in the branches of content creation and marketing alongside her studies. She is the head of the Cytolytics blog and could already gather experience in writing medical articles for various magazines. Her interests are recent health issues and news about medicine, health technologies, and digital health.
flowcytometry &cytolytics (7)

Blood Cancer

In Germany, one person receives the devastating diagnosis of blood cancer every 15 minutes. Many patients are children and adolescents, but older people are also frequently affected. This form of cancer is rather rare compared to other cancers. But what exactly is blood cancer? How well can blood cancer be diagnosed and what treatment options are available?

What is blood cancer (leukemia)?

Many people colloquially refer to leukemias as blood cancers. Strictly speaking, however, leukemias are diseases of the blood-forming system. This means that not only the blood is affected, but mainly the bone marrow or the lymphatic organs. The consequence of leukemia is disturbed blood formation due to the uncontrolled multiplication of malignant blood cells. As a result of these cancer cells, the blood can no longer perform its vital tasks, such as fighting infections, transporting oxygen, or stopping bleeding. Also, these altered leukemia cells can spread throughout the body via the blood and, for example, also affect and damage the nervous system and internal organs.

What are the different forms of leukemia?

Doctors and researchers divide leukemia diseases into leukemic cells based on their gene alteration and into lymphocytic and myeloid leukemias based on the type of cells affected. These special designations are used only to distinguish the affected cell line of origin. Besides, there is a further classification according to the course of the disease. There is an additional distinction between acute and chronic leukemias:

Myeloid leukemias: originate from the precursor cells of granulocytes (are responsible for our “innate” immune defenses), and by extension, erythrocytes (our red blood cells) and platelets (essential for intact blood clotting).

Lymphocytic leukemias: affect lymphocytes (are responsible for our “acquired” immune defenses) and their precursor cells.

Acute leukemia: occurs suddenly with severe disease symptoms and are life-threatening diseases that lead to death in a few weeks to months if left untreated.

Chronic leukemia: it can take months or years for the affected person to suffer from the first symptoms.

All of these four forms can present in combinations with different symptoms and courses:

Acute myeloid leukemia (AML): most common acute leukemia, starts quite suddenly and progresses rapidly and about half of the patients are older than 70 years.

Chronic myeloid leukemia (CML): has a slow, insidious course (with exceptions), the median age of onset is 50 to 60 years, and occurs very rarely in children.

Acute lymphoblastic leukemia (ALL): most common of all forms of leukemia, starts quite suddenly and progresses rapidly and occurs mainly in children (ALL is the most common type of cancer in children) and otherwise in adult patients usually older than 80 years.

Chronic lymphocytic leukemia (CLL): most common leukemia in adults with slow and insidious progression, the median age of onset is 70 to 75 years old

and does not belong to the “true” leukemias, but lymphatic cancers (malignant lymphomas).

What are the causes of the different leukemia diseases?

The causes of the various forms of blood cancer have not yet been identified. However, experts have identified several risk factors that favor the development of leukemia. These include genetic predisposition, age, smoking, radioactive or X-ray radiation, chemical substances such as benzene or insecticides, or even very rare viruses.

How can leukemia be diagnosed?

Symptoms such as reduced performance, pallor, palpitations, frequent nosebleeds, or persistent fever are often unspecific and often occur in many other and sometimes harmless diseases. Therefore, they are not always taken seriously right away. However, with such complaints, there is always a suspicion of leukemia. In many cases, it is possible to make a detailed diagnosis with the help of immunophenotyping alone, while in other cases an additional examination of the bone marrow or molecular pathological examinations are necessary. Immunophenotyping is performed by flow cytometry, which allows rapid diagnosis. In this examination, leukocytes are stained and sorted using immunological markers. Differentiated and accurate differentiation of individual leukocytes by function and stage of maturation is achieved. Due to its high sensitivity, flow cytometry is becoming increasingly important in staging (assessment of tumor extent) examinations of the blood and bone marrow and can thus help to design therapy options that are appropriate for the patient.

What are the treatment options for leukemia?

Leukemia treatment is individually adapted to each patient. Various factors play a role in this. In addition to the patient’s age and general state of health, the course of the disease (acute or chronic) is particularly important. The therapy then ranges accordingly from chemotherapy to immunotherapy to stem cell transplantation. Depending on the cells affected, the therapy is tailored to the patient, which is why immunophenotyping is highly relevant. Also, possible side effects such as increased susceptibility to infections, nausea, and pain are treated appropriately with special drugs. Patients are also examined regularly during and after therapy. If there is a relapse, the cancer cells can be detected early in this way using flow cytometry. Besides, follow-up care is concerned with treating any long-term consequences of the previous therapy.

About the author
Elif Karakurt
medical content creator
Elif is a medical student and works for Cytolytics in the branches of content creation and marketing alongside her studies. She is the head of the Cytolytics blog and could already gather experience in writing medical articles for various magazines. Her interests are recent health issues and news about medicine, health technologies, and digital health.
flowcytometry &cytolytics (6)

AI Applications in Medicine

Humans see and hear, we make plans, and we adapt to change. Artificial intelligence (AI) is when we replicate such cognitive performances on machines or computers. However, we still don’t know in detail how our brains do these things. But we can think of mathematical procedures that perform similar tasks in certain areas. With algorithms, machines can use sample data and derive models from them to improve their behavior step by step. From chess or other brainteasers on the Internet, the duel of man against machine has been one of the classics for years. On the one hand, it fascinates us to see how computers and machines learn on their own and adapt their behavior without human intervention. They are getting better and better and are already superior to us in some cases – just a few days ago, a computer beat five poker pros at once for the first time. This potential must be exploited, also in the field of medicine, where many treatment methods are becoming better and better through the use of intelligent software. Whether it’s apps for the early detection of diseases or personalized cancer therapies: Intelligent systems are expanding the possibilities of the medical profession quite considerably. On the other hand, there are still some challenges to be overcome, which AI brings with it. Is it ethical to listen to a machine in sensitive matters of life and death? What framework do we provide so that technology always serves people – and not the other way around?

What is AI capable of?

Self-learning algorithmic systems do nothing other than independently search for patterns in a huge pile of data that humans would not recognize or would recognize only with the greatest effort. Therefore, such learning systems are particularly suitable for repetitive tasks such as searching for anomalies, deviations, or commonalities and can also generate meaningful results from new data, i.e. they do not have to be reprogrammed every time. For example, in computed tomography scans, which doctors have hundreds of in hospitals every day, or blood cancer diagnostics by evaluating blood samples using flow cytometry after hours of gating. Through appropriate software development, AI technologies provide valuable services in medical diagnosis and therapy.

Where are the opportunities for AI in medicine?

AI brings enormous advantages. First, they can recognize relevant patterns that humans might never have looked for in the first place. Moreover, unlike humans, they never get tired or frustrated. They work without rest and can theoretically be fed with more data indefinitely because they learn at will. AI algorithms thus relieve humans of the very activities that dehumanize them. Numerous studies impressively prove that AI systems are very good at this and – for example – can reliably evaluate images. A study from Stanford, for example, showed that self-learning algorithms can classify skin cancer as competently or even better than dermatologists. Another field of application is personalized medicine. Here, for example, gene expression data is evaluated on an AI basis to arrive at tailored therapy recommendations. AI is also making inroads in the field of robotics. Medical robots or nursing robots can benefit from AI and become more autonomous. To improve healthcare, increasing patients’ chances of recovery, and supporting doctors in their diagnoses and therapy decisions, AI will increasingly become a part of healthcare in the future. The basic prerequisite for AI applications is data – including patient data, for example from the planned electronic patient record.

What are the prerequisites and framework conditions for AI?

The technical and organizational conditions required for the quality-assured use of AI assistance systems in medicine include the certification of AI systems and access control mechanisms to protect against attacks, as well as the integrity of data records and secure transmission paths. There are still several potential hurdles to overcome on the road to the widespread use of AI medical devices. First and foremost is a secure and powerful IT infrastructure for the storage and transmission of healthcare data and the digitization of care processes. To make this data accessible, it is necessary to establish suitable care registers for research and development purposes. There is a considerable need to catch up in this area in Germany. It is to be hoped that the laws currently on the way, above all the Hospital Future Act, the Digital Care Act, and the Patient Data Protection Act, will have the intended effect.

What are the prospects for AI?

Despite the above-mentioned challenges, it is already becoming apparent that artificial intelligence has become a key technology. It will help to overcome the current challenges facing the healthcare sector. Above all, AI ensures that diseases are detected more precisely and earlier. The quality and affordability of medical care should benefit from this.

About the author
Elif Karakurt
medical content creator
Elif is a medical student and works for Cytolytics in the branches of content creation and marketing alongside her studies. She is the head of the Cytolytics blog and could already gather experience in writing medical articles for various magazines. Her interests are recent health issues and news about medicine, health technologies, and digital health.